The Use of AI To Improve Leadership Development
Leadership development is a critical requirement of contemporary organisational managements for the maintenance and enhancement of competitive advantage. Business firms are trying to ensure their capabilities in keeping up with the swift and continuous evolution of their workplaces, mainly because of Industry 4.0, i.e. the present day trend of automation with the help of data exchange and machine learning.
Leadership development helps in maintaining organisational dimension and ensuring that businesses are relevant and profitable. Notwithstanding the increasing focus on leadership development, surveys reveal that the leadership development programmes of 60% of US firms were not allied with their business needs. Such development programmes help organisations by creating competent and empowered leaders, improving organisational innovation, detailing talent, augmenting customer retention, driving change management and enhancing financial profitability.
Artificial Intelligence is the ability of a computer or a computer controlled robot to carry out actions that are usually done by humans with their inherent intelligence and discernment. AI ensures that machines can learn from experience, absorb new inputs and perform like humans; computers proficient in chess and self-driving vehicles depend substantially on deep learning and natural language processing in order to function effectively.
Leadership development is currently being implemented by organisational managements with the help of various tools and techniques, especially in areas of strategic thinking, decision making, conflict resolution, team building and delegation. The mechanisms used for this purpose include (1) formal instruction, (2) self-directed learning, (3) executive coaching, (4) 360 degree feedback and (5) carefully thought-out job assignments. Contemporary management thinkers iterate that AI has to be used ever more in leadership development programmes because of its utility in enhancement of diagnostic skills, complex environmental simulation, number crunching, talent identification, and leader selection, amongst others. With both leadership development and Artificial Intelligence being critical for organisational progress in future, the application of AI in leadership development constitutes an important topic for research.
Contemporary Leadership Development
Whilst considerable money is spent on leadership development by professional and competitive organisations, a recent survey by Harvard University revealed that the majority of company leadership development programmes were inadequately aligned with business requirements in the increasingly complex contemporary environment. Only 19% of the organisations stated that they were effectively developing leaders for the future and 71% stated that their leaders may not be capable of leading their organisations in the coming periods. The examination of leadership development criticality informed that leadership in the 4.0 environment was similar to a successful ecosystem, rather than the orthodox and bureaucratic business structure of earlier generations. Leadership structures were becoming flatter and businesses were being compelled to evolve in order to remain relevant and profitability.
Day and Sin (2011) informed that leadership development leads to the creation of skilled and empowered leaders. Whilst organisational leaders may appear to be extremely busy, their activities may be focused on management activities like planning, budgeting and systems, rather than on leadership, the visualisation of the future and the implementation of relevant and necessary organisational change (DeRue & Ashford, 2010). Industry 4.0 calls for a shift in leadership thinking from siloed leadership to distribution, collaboration and teamwork (DeRue et al., 2012).
CHART 1: THE CHANGING NATURE OF LEADERSHIP (Source: Riggio & Mumford, 2011)
Ahlquist, (2014) informed that contemporary companies require greater use of innovative learning techniques in leadership development programmes. Successful leaders should refrain from depending upon their positions to inspire productivity and instead focus on inspiring people to beneficial larger visions (Smith & Green, 2018). They should serve as mentors and coaches to internal talent and stress on greater empathy in education and development of their team members (Smith & Green, 2018).
Leadership development programmes should provide people with important leadership skills, especially in areas like communication, motivation, inspiration, decision making, accountability, sustainability and the running of ethical organisations (DeRue et al., 2012). Research has specifically revealed that employee retention is much more in organisations that focus on leadership development (Dragoni et al., 2009). The development of people with regard to their creativity, leadership skillsets and talent engagement improves productivity, collaboration and overall work satisfaction (DeRue et al., 2012).
Use of AI in Leadership Development
Artificial Intelligence enables machines to obtain inputs and learn from experience, make suitable adjustments and carry out human like tasks. Machine learning and natural language processing, two important elements of AI can help in training computers to achieve particular tasks by (1) processing substantial quantities of data and (2) recognising data patterns. Conceptualised in 1956, AI has been powered by advances in algorithms, improvements in computing power and storage and enhancement in data volumes. Machine learning became popular during the period 1980 to 2010 and deep learning is driving the AI boom in the present day. AI automates repetitive learning and discovery through data by performing frequent high volume and computerised tasks with reliability and without tiredness/fatigue. It adds intelligence to existing products. Automation along with smart machines, bots and conversational platforms can be operated with considerable volumes of data in order to enhance several technologies (Naqvi & Munoz, 2018).
AI adapts through the use of progressive learning algorithms so that the data can be itself improve the programming. It finds structures and regularities and structure in data and thereby facilitates algorithms in the acquisition of skills. It analyses greater amounts and deeper data by applying neural networks with several concealed layers. The use of deep neural networks enables AI to generate tremendous accuracy.
Organisations can make use of AI to identify and select talent and thereby overcome the current challenges of assumptions, heuristics and cognitive biases that undermine leadership selection. Several applications available in the market are currently using some form of AI to enhance talent decisions. Games are being used to assess and evaluate decision making preferences and cognitive ability. Social media and video interviews are being used to mine prosody, i.e. the patterns of intonation and stress in a language. The use of such apps can help HR managers and organisational leaders in the accurate identification of talent and considerable scale, with swiftness and objectivity (Terblanche, 2020).
Whilst several organisations are using AI for identification and development of leadership in junior and middle management roles, efforts are being made to use them to build strong executive and senior leadership (Naqvi & Munoz, 2018). AI can also be trained to ignore demographic factors and focus on the identification of the qualities, characteristics and skills required for becoming successful leaders (Rouhiainen, 2018). Data driven tools, which leverage technologies, like for example, chatbots and AI powered assistants have the power to increase the self-awareness of people and provide them with real-time and personalised feedback on becoming a better leader (Plastino & Purdy, 2018). There seems to be little doubt that AI can be used as a very powerful tool for enhancement of leadership development.
References
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Dragoni, L., Tesluk, P. E., Russell, J.E.A., & Oh, I. S., (2009), “Understanding managerial development: Integrating developmental assignments, learning orientation, and access to developmental opportunities in predicting managerial competencies”, Academy of Management Journal, 52: 731–743.
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